Citrus Fruit Classification

Authors

  • Sonia Stanley Louis Student, Department of Electronics and Communication Engineering, K. S. Institute of Technology, Bangalore, India
  • D. S. Hemalatha Student, Department of Electronics and Communication Engineering, K. S. Institute of Technology, Bangalore, India
  • S. Meghana Student, Department of Electronics and Communication Engineering, K. S. Institute of Technology, Bangalore, India
  • J. S. Saraswathi Student, Department of Electronics and Communication Engineering, K. S. Institute of Technology, Bangalore, India
  • G. R. Sunil Kumar Assistant Professor, Department of Electronics and Communication Engineering, K. S. Institute of Technology, Bangalore, India

Keywords:

RGB color space, Raspberry pi kit, Citrus filter, Thresholding, Mean filter, Pixel classification counter

Abstract

Usually in the citrus industries, fruit grading is performed by humans through visual inspection. Manual inspection implies several problems in maintaining grading consistency and sorting uniformity. Citrus classification is normally achieved based on external visible criteria, such as size, shape and color. This problem has been addressed using computer vision algorithms, but an automatic grading machine based on computer vision usually requires large computational resources in order to perform the classification due to the complexity of the computer vision operators. This paper describes an embedded color-based citrus selection system implemented on a raspberry pi device.

Downloads

Download data is not yet available.

Downloads

Published

28-07-2020

Issue

Vol. 3 No. 7 (2020)

Section

Articles

License

Copyright (c) 2020 Sonia Stanley Louis, D. S. Hemalatha, S. Meghana, J. S. Saraswathi, G. R. Sunil Kumar

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
S. S. Louis, D. S. Hemalatha, S. Meghana, J. S. Saraswathi, and G. R. S. Kumar, “Citrus Fruit Classification”, IJRESM, vol. 3, no. 7, pp. 330–332, Jul. 2020, Accessed: May 09, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/91